系统农业：结合农业社会经济属性的建模和控制

doi:10.11959/j.issn.2096-6652.202306

智能科学与技术学报 ›› 2023, Vol. 5 ›› Issue (1): 41-50.doi: 10.11959/j.issn.2096-6652.202306

系统农业：结合农业社会经济属性的建模和控制

康孟珍¹^,², 孙贺全³^,⁴^,⁵, 王秀娟¹^,⁶, 王飞跃¹^,²

¹ 中国科学院自动化研究所多模态人工智能系统全国重点实验室，复杂系统管理与控制国家重点实验室，北京 100190
² 中国科学院大学人工智能学院，北京 100049
³ 马克斯·普朗克植物育种研究所，德国科隆 D-50829
⁴ 慕尼黑大学遗传学研究所，德国慕尼黑 D-82152
⁵ 西安交通大学电信学部自动化科学与工程学院，陕西西安 710049
⁶ 中国科学院自动化研究所北京智能技术工程研究中心，北京 100190

修回日期:2023-02-20 出版日期:2023-03-15 发布日期:2023-03-01
作者简介:康孟珍（1975- ），女，中国科学院自动化研究所复杂系统管理与控制国家重点实验室副研究员，主要研究方向为平行农业、计算植物
孙贺全（1982- ），男，马克斯·普朗克植物育种研究所、慕尼黑大学（德国）遗传学研究所生物信息学研究员，主要研究方向为计算生物学、作物基因组学
王秀娟（1982- ），女，中国科学院自动化研究所复杂系统管理与控制国家重点实验室助理研究员，主要研究方向为平行农业、植物建模
王飞跃（1961- ），男，中国科学院自动化研究所复杂系统管理与控制国家重点实验室主任，主要研究方向为平行系统的方法与应用、社会计算、平行智能、知识自动化
基金资助:
国家重点研发计划资助项目(2021ZD0113704);国家自然科学基金资助项目(62076239)

Systems agriculture: modeling and control based on social and economic attributes of agriculture

Mengzhen KANG¹^,², Hequan SUN³^,⁴^,⁵, Xiujuan WANG¹^,⁶, Fei-Yue WANG¹^,²

¹ State Key Laboratory of Multimodal Artificial Intelligence Systems, State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
² School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
³ Max Planck Institute for Plant Breeding Research, Cologne D-50829, Germany
⁴ Faculty of Biology, LMU Munich, Munich D-82152, Germany
⁵ School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an 710049, China
⁶ Beijing Engineering Research Center of Intelligent Systems and Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China

Revised:2023-02-20 Online:2023-03-15 Published:2023-03-01
Supported by:
The National Key Research and Development Program of China(2021ZD0113704);The National Natural Science Foundation of China(62076239)

摘要/Abstract

摘要：

随着第五次工业革命的到来与发展，生物科技、信息技术与人工智能深度融合，为发展信息化、智能化的农业提供了强有力的支持。由于农业具有社会经济属性，面向具有生物物理特性的种植系统及具有经济社会特性的管理系统，构建农业社会物理信息系统已成为共识。在系统生物学启示下，提出系统农业，即基于平行农业框架，结合农村、农民两个维度构建农业系统，以生物、信息、人工智能等技术为支撑，监测和整合多尺度、多维度、多模态信息，依据系统理论展开涵盖农业、农村、农民的系统农业研究，服务未来乡村发展。对系统农业涉及的智能技术及具体案例进行了总结与分析，并对系统农业的未来发展趋势进行了展望。

关键词: 平行系统, ACP理论, DAOs, 农业元宇宙

Abstract:

With the arrival and development of the fifth industrial revolution, biotechnology, information technology and artificial intelligence are deeply integrated.This provides strong support for the informatization and intelligentization of agriculture.Due to the social and economic characteristics of agriculture, it has become a consensus to build an agricultural physical and social information system toward both the planting system with biophysical properties and the management system with socio-economic properties.Inspired by systems biology, systems agriculture was proposed, which combined two other dimensions of villages and farmers information using the parallel agriculture framework to build and study the agricultural system.Supported by biotechnology, information technology and artificial intelligence technology, systems agriculture had involved monitoring and integrating multi-scale, multi-dimensional and multimodal information, and carried out systematic research covering agriculture, villages and farmers using systems theory, in order to serve the development of future villages.The intelligent technology and the specific cases involved in systems agriculture were summarized and analyzed, and the perspectives of systems agriculture were presented.

Key words: parallel system, ACP theory, DAOs, agricultural metaverse

中图分类号:

康孟珍, 孙贺全, 王秀娟, 等. 系统农业：结合农业社会经济属性的建模和控制[J]. 智能科学与技术学报, 2023, 5(1): 41-50.

Mengzhen KANG, Hequan SUN, Xiujuan WANG, et al. Systems agriculture: modeling and control based on social and economic attributes of agriculture[J]. Chinese Journal of Intelligent Science and Technology, 2023, 5(1): 41-50.

图/表 5

参考文献 45

[1]	ALEXANDRATOS N , . How to feed the world in 2050[C]// Proceedings of High-Level Expert Forum.[S.l.:s.n.], 2009.
[2]	TARDIEU F , CABRERA-BOSQUET L , PRIDMORE T ,et al. Plant phenomics,from sensors to knowledge[J]. Current Biology, 2017,27(15): R770-R783.
[3]	赵春江 . 植物表型组学大数据及其研究进展[J]. 农业大数据学报, 2019,1(2): 5-18.
	ZHAO C J . Big data of plant phenomics and its research progress[J]. Journal of Agricultural Big Data, 2019,1(2): 5-18.
[4]	ZHANG C Z , YANG Z M , TANG D ,et al. Genome design of hybrid potato[J]. Cell, 2021,184(15): 3873-3883.
[5]	YANG W Y , GUO T T , LUO J Y ,et al. Target-oriented prioritization:targeted selection strategy by integrating organismal and molecular traits through predictive analytics in breeding[J]. Genome Biology, 2022,23(1): 1-19.
[6]	康孟珍, 王秀娟, 华净 ,等. 平行农业:迈向智慧农业的智能技术[J]. 智能科学与技术学报, 2019,1(2): 107-117.
	KANG M Z , WANG X J , HUA J ,et al. Parallel agriculture:intelligent technology toward smart agriculture[J]. Chinese Journal of Intelligent Science and Technology, 2019,1(2): 107-117.
[7]	王飞跃 . 关于复杂系统的建模、分析、控制和管理[J]. 复杂系统与复杂性科学, 2006,3(2): 26-34.
	WANG F Y . On the modeling,analysis,control and management of complex systems[J]. Complex Systems and Complexity Science, 2006,3(2): 26-34.
[8]	KANG M Z , WANG F Y . From parallel plants to smart plants:intelligent control and management for plant growth[J]. IEEE/CAA Journal of Automatica Sinica, 2017,4(2): 161-166.
[9]	STRINGER L C , FRASER E D G , HARRIS D ,et al. Adaptation and development pathways for different types of farmers[J]. Environmental Science ＆ Policy, 2020,104: 174-189.
[10]	LOWDER S K , SKOET J , RANEY T . The number,size,and distribution of farms,smallholder farms,and family farms worldwide[J]. World Development, 2016,87: 16-29.
[11]	PRETTY J , ATTWOOD S , BAWDEN R ,et al. Assessment of the growth in social groups for sustainable agriculture and land management[J]. Global Sustainability, 2020,3.
[12]	温铁军, 梁少雄, 刘良 . 乡建笔记:新青年与乡村的生命对话[M]. 北京: 东方出版社, 2020:396.
	WEN T J , LIANG S X , LIU L . Rural construction notes:dialogue of life between the new youth and the village[M]. Beijing: Oriental Press, 2020:396.
[13]	CUI Z L , ZHANG H Y , CHEN X P ,et al. Pursuing sustainable productivity with millions of smallholder farmers[J]. Nature, 2018,555(7696): 363-366.
[14]	FAN M H , KANG M Z , WANG X J ,et al. Parallel crop planning based on price forecast[J]. International Journal of Intelligent Systems, 2022,37(8): 4772-4793.
[15]	BERTALANFFY L V , WOODGER J H . Modern theories of development:an introduction to theoretical biology[M]. London: Oxford University Press, 1933.
[16]	LINNéC V . Systema naturae in quo naturae regna tria,secundum classes,ordines,genera,species,systematice,proponuntur[M]. Stockholmiae:Apud G. 1740.
[17]	MESAROVI?M D , . Systems theory and biology—view of a theoretician[C]// Proceedings of systems theory and biology. Heidelberg:Springer, 1968: 59-87.
[18]	LANDER E S , LINTON L M , BIRREN B ,et al. Initial sequencing and analysis of the human genome[J]. Nature, 2001,409(6822): 860-921.
[19]	BOOGERD F C . Systems biology:philosophical foundations[M]. Amsterdam: Elsevier, 2007.
[20]	钱学森, 于景元, 戴汝为 . 一个科学新领域:开放的复杂巨系统及其方法论[J]. 自然杂志, 1990,12(1): 3-10,64.
	QIAN X S , YU J Y , DAI R W . A new field of science—open complex giant system and its methodology[J]. Nature Magazine, 1990,12(1): 3-10,64.
[21]	SURAVAJHALA P , KOGELMAN L J A , KADARMIDEEN H N . Multi-omic data integration and analysis using systems genomics approaches:methods and applications in animal production,health and welfare[J]. Genetics Selection Evolution, 2016,48(1): 1-14.
[22]	KEATING B A , MCCOWN R L . Advances in farming systems analysis and intervention[J]. Agricultural Systems, 2001,70(2/3): 555-579.
[23]	KANG M Z , FAN X R , HUA J ,et al. Managing traditional solar greenhouse with CPSS:a just-for-fit philosophy[J]. IEEE Transactions on Cybernetics, 2018,48(12): 3371-3380.
[24]	华净, 王秀娟, 王浩宇 ,等. 基于物联网的日光温室环境监测在线校准[J]. 中国农学通报, 2020,36(5): 120-124.
	HUA J , WANG X J , WANG H Y ,et al. Online calibration of environmental monitoring in solar greenhouse based on internet of things[J]. Chinese Agricultural Science Bulletin, 2020,36(5): 120-124.
[25]	HUA J , WANG X J , WANG H Y ,et al. Prediction of crop phenology—a component of parallel agriculture management[C]// Proceedings of 2017 Chinese Automation Congress. Piscataway:IEEE Press, 2018: 7704-7708.
[26]	FAN X R , KANG M Z , HEUVELINK E ,et al. A knowledge-and-data-driven modeling approach for simulating plant growth:a case study on tomato growth[J]. Ecological Modelling, 2015,312: 363-373.
[27]	TAWSEEF SHAIKH A , TABASUM R , FAISAL R L . Towards leveraging the role of machine learning and artificial intelligence in precision agriculture and smart farming[J]. Computers and Electronics in Agriculture, 2022,198.
[28]	SUBEESH A , MEHTA C R . Automation and digitization of agriculture using artificial intelligence and internet of things[J]. Artificial Intelligence in Agriculture, 2021,5: 278-291.
[29]	韩佳伟, 朱文颖, 张博 ,等. 装备与信息协同促进现代智慧农业发展研究[J]. 中国工程科学, 2022,24(1): 55-63.
	HAN J W , ZHU W Y , ZHANG B ,et al. Equipment and information collaboration to promote development of modern smart agriculture[J]. Strategic Study of CAE, 2022,24(1): 55-63.
[30]	SHAIKH T A , AHMAD MIR W , RASOOL T ,et al. Machine learning for smart agriculture and precision farming:towards making the fields talk[J]. Archives of Computational Methods in Engineering, 2022,29(7): 4557-4597.
[31]	YUAN S W , L X , DU E H . Effects of farmers’ behavioral characteristics on crop choices and responses to water management policies[J]. Agricultural Water Management, 2021,247.
[32]	王秀娟, 康孟珍, 华净 ,等. 从群体到个体尺度——基于数据的DSSAT和GreenLab作物模型连接探索[J]. 智慧农业(中英文), 2021,3(2): 77-87.
	WANG X J , KANG M Z , HUA J ,et al. From stand to organ level—a trial of connecting DSSAT and GreenLab crop model through data[J]. Smart Agriculture, 2021,3(2): 77-87.
[33]	VOS J , EVERS J B , BUCK-SORLIN G H , ,et al. Functional-structural plant modelling:a new versatile tool in crop science[J]. Journal of Experimental Botany, 2010,61(8): 2101-2115.
[34]	DE REFFYE P , HU B G , KANG M Z ,et al. Two decades of research with the GreenLab model in agronomy[J]. Annals of Botany, 2021,127(3): 281-295.
[35]	PENG B , GUAN K Y , CHEN M ,et al. Improving maize growth processes in the community land model:implementation and evaluation[J]. Agricultural and Forest Meteorology, 2018,250/251: 64-89.
[36]	WANG X H , ZHAO C , MüLLER C , ,et al. Emergent constraint on crop yield response to warmer temperature from field experiments[J]. Nature Sustainability, 2020,3(11): 908-916.
[37]	WENG Y C , WANG X J , HUA J ,et al. Greenhouse environment control based on computational experiments[C]// Proceedings of 2020 4th High Performance Computing and Cluster Technologies Conference ＆ 2020 3rd International Conference on Big Data and Artificial Intelligence. New York:ACM Press, 2020.
[38]	WENG Y C , WANG X J , HUA J ,et al. Forecasting horticultural products price using ARIMA model and neural network based on a large-scale data set collected by web crawler[J]. IEEE Transactions on Computational Social Systems, 2019,6(3): 547-553.
[39]	庄家煜, 许世卫, 李杨 ,等. 基于深度学习的多种农产品供需预测模型[J]. 智慧农业, 2022,4(2): 174-182.
	ZHUANG J Y , XU S W , LI Y ,et al. Supply and demand forecasting model of multi-agricultural products based on deep learning[J]. Smart Agriculture, 2022,4(2): 174-182.
[40]	LAKSHMANAN V I , CHOCKALINGAM A , MURTY V K ,et al. Smart villages:bridging the global urban-rural divide[M]. Cham: Springer Nature Switzerland AG, 2020.
[41]	吕普生 . 数字乡村与信息赋能[J]. 中国高校社会科学, 2020(2): 69-79,158.
	LYU P S . Digital Village and information empowerment[J]. Social Sciences in Chinese Higher Education Institutions, 2020(2): 69-79,158.
[42]	康孟珍, 王秀娟, 李冬 ,等. 基于联邦学习的分布式农业组织[J]. 智能科学与技术学报, 2022,4(2): 288-297.
	KANG M Z , WANG X J , LI D ,et al. Distributed agricultural organization based on federated learning[J]. Chinese Journal of Intelligent Science and Technology, 2022,4(2): 288-297.
[43]	WANG X J , KANG M Z , SUN H Q ,et al. DeCASA in AgriVerse:parallel agriculture for smart villages in metaverses[J]. IEEE/CAA Journal of Automatica Sinica, 2022,9(12): 2055-2062.
[44]	KANG M Z , WANG X J , WANG H Y ,et al. The development of AgriVerse:past,present,and future[J]. IEEE Transactions on Systems,Man,and Cybernetics:Systems, 2023(99): 1-10.
[45]	WANG F Y . Parallel intelligence in metaverses:welcome to Hanoi![J]. IEEE Intelligent Systems, 2022,37(1): 16-20.

系统农业：结合农业社会经济属性的建模和控制

Systems agriculture: modeling and control based on social and economic attributes of agriculture

在线阅读

PDF下载

可视化

摘要/Abstract

引用本文

使用本文

图/表 5

参考文献 45

相关文章 15

Metrics

推荐阅读 0

[1]	缪青海, 吕宜生. 元宇宙下的平行交通系统[J]. 智能科学与技术学报, 2023, 5(1): 32-40.
[2]	王晓, 杨林瑶, 胡斌, 侯家琛. 平行推理：一种基于ACP方法的虚实互动的知识协同框架[J]. 智能科学与技术学报, 2023, 5(1): 69-82.
[3]	田永林, 陈苑文, 杨静, 王雨桐, 王晓, 缪青海, 王子然, 王飞跃. 元宇宙与平行系统：发展现状、对比及展望[J]. 智能科学与技术学报, 2023, 5(1): 121-132.
[4]	康孟珍, 邱文忠, 陈自富, 王猛, 许沙沙, 王秀娟, 倪爱东, 蒋玉洁, 陈世超, DEREFFYE Philippe, 王飞跃. 平行圆明园：从数字孪生园林到元宇宙智慧遗址公园[J]. 智能科学与技术学报, 2022, 4(3): 301-307.
[5]	郭超, 鲁越, 王晓, 易达, 王虓, 王飞跃. 人机物CPSS智能融合的平行创作架构与关键技术研究[J]. 智能科学与技术学报, 2022, 4(3): 344-354.
[6]	李小双, 王晓, 杨林瑶, 田永林, 王雨桐, 张俊, 王飞跃. 元电网MetaGrid：基于平行电网的新一代智能电网的体系与架构[J]. 智能科学与技术学报, 2021, 3(4): 387-398.
[7]	李亚玲, 杨林瑶, 葛俊, 覃缘琪, 王晓. 博弈5.0：基于平行系统和机器博弈的社会认知平行博弈[J]. 智能科学与技术学报, 2021, 3(4): 507-520.
[8]	王飞跃, 蒋怀光. 平行电池：智能生态化电池技术与服务体系的框架和流程[J]. 智能科学与技术学报, 2021, 3(4): 521-531.
[9]	王春法, 王飞跃, 鲁越, 李华飙, 郭超. 平行博物馆：新时代博物馆运营的智能管理与控制[J]. 智能科学与技术学报, 2021, 3(2): 125-136.
[10]	吴宇震, 张俊, 高天露, 孙玉健, 刘金旭. 平行港口：智慧绿色时代下港口工业智联网新形态与体系结构[J]. 智能科学与技术学报, 2021, 3(2): 218-227.
[11]	王飞跃. 平行控制与数字孪生：经典控制理论的回顾与重铸[J]. 智能科学与技术学报, 2020, 2(3): 293-300.
[12]	李浥东,张俊,陶耀东,王伟,顾元祥,王飞跃. 平行安全：基于CPSS的生成式对抗安全智能系统[J]. 智能科学与技术学报, 2020, 2(2): 194-202.
[13]	郭超,鲁越,林懿伦,卓凡,王飞跃. 平行艺术：人机协作的艺术创作[J]. 智能科学与技术学报, 2019, 1(4): 335-341.
[14]	宁滨. 平行轨道交通系统[J]. 智能科学与技术学报, 2019, 1(3): 215-218.
[15]	张远馨,周明,王深艳,梁珍珍,丁文文,王晓. 面向在线餐饮外卖垃圾治理的智能可持续生态系统工程模型研究[J]. 智能科学与技术学报, 2019, 1(3): 287-304.